Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jscraik/Agent-Skills --skill originalgit clone --depth 1 https://github.com/jscraik/Agent-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jscraik/agent-skills/original)<a href="https://agentmods.dev/skills/jscraik/agent-skills/original"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/original/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jscraik/agent-skills/original"><img src="https://agentmods.dev/badge/skills/jscraik/agent-skills/original.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.05078 |
| Opus 5.5 | $0.00018 | $0.02031 |
| Sonnet 5.5 | $0.00009 | $0.01016 |
| Haiku 4.5 | $0.00004 | $0.00508 |
Grade A, and why
agents-md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 307 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents Md
Create and maintain concise, high-signal AGENTS guidance with progressive disclosure.
Table of Contents
- When to use
- Standards snapshot
- Required inputs
- Discovery interview
- Response format
- Deliverables
- Failure mode
- Philosophy
- Constraints
- Procedure
- Validation
- Project-tailored repo baseline
- Anti-patterns
- Variation
- AGENTS.md Template Guidance
- Mandatory workflow snippet
- Examples
- Resource map
- Decision Quality Feedback
When to use
- Use this skill when the user asks to create or update
AGENTS.md. - Use this skill when AGENTS docs are too large, duplicated, or contradictory.
- Use this skill when instruction routing needs to be split into linked files.
- Use this skill when a repo needs AGENTS operating rules such as preflight, stack detection, tooling, required paths, Local Memory policy, Project Brain policy, or startup workflow tailored from real repo evidence.
- Use this skill when the user wants the project's instruction surface audited so required instruction files are present, current, correctly routed, and accurately disclosed.
Standards snapshot (April 2026)
Use this section as an adaptation guideline for generated AGENTS.md files, not runtime policy.
- Keep root
AGENTS.mdminimal and route depth into linked docs. - Start with 2-3 focused surfaces for a first pass: usually the root
AGENTS.md, one linked-doc tree, and only one nested override if it is truly needed. - Teach the canonical discovery chain: global
AGENTS.override.mdorAGENTS.md, then per-directoryAGENTS.override.md,AGENTS.md, then configured fallback filenames. - Treat only one auto-loaded instruction file per directory as canonical; linked docs are progressive-disclosure references, not implicitly discovered project instructions.
- Keep combined project guidance under the
project_doc_max_bytesbudget (32 KiB default) by splitting large guidance across nested scopes instead of bloating one root file. - Instruction budget: frontier thinking models can reliably follow ~150–200 instructions. Every token in
AGENTS.mdloads on every request regardless of relevance, so every instruction must earn its place. - Minimum viable floor: the root file needs only three things — a one-sentence project description, the package manager if not npm, and any non-standard build/typecheck commands. Everything else is a candidate for progressive disclosure.
- Staleness is poison: avoid documenting file paths in
AGENTS.md; they change constantly and agents read stale paths confidently. Describe capabilities and where things might be rather than hardcoding structure. - Never auto-generate AGENTS.md files; generated files flood the budget with generic instructions that hurt performance. Write them intentionally.
- When harmonizing
AGENTS.md,CLAUDE.md, andGEMINI.md, keep shared operational rules semantically aligned while respecting each tool's official instruction-file model and section conventions. For cross-tool coverage, aln -s AGENTS.md CLAUDE.mdsymlink is a valid low-maintenance option when Claude Code is in scope. - Base commands, paths, and conventions on verified repo evidence only.
- Treat contradiction detection and instruction precedence as first-class outputs.
- Prefer progressive disclosure over megadoc accumulation.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 307 lines · 44 tokens per session scan A 3341f17a32af
agents-md is a skill published in the GitHub repository jscraik/Agent-Skills (9 stars, last pushed 4d ago), licensed Apache-2.0. It adds 44 tokens to every session and 5,078 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-13.
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